Statistical shape analysis of brain structures using spherical wavelets

D. Nain; M. Styner; M. Niethammer; J. J. Levitt; M. E. Shenton; G. Gerig; A. Bobick; A. Tannenbaum

doi:10.1109/ISBI.2007.356825

Statistical shape analysis of brain structures using spherical wavelets

D. Nain, M. Styner, M. Niethammer, J. J. Levitt, M. E. Shenton, G. Gerig, A. Bobick, A. Tannenbaum

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions.

Original language	English (US)
Title of host publication	2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro - Proceedings
Pages	209-212
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2007.356825
State	Published - 2007
Event	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States Duration: Apr 12 2007 → Apr 15 2007

Publication series

Name	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other	2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Country/Territory	United States
City	Arlington, VA
Period	4/12/07 → 4/15/07

Keywords

Image shape analysis
Wavelet transforms

ASJC Scopus subject areas

Electrical and Electronic Engineering
General Medicine

Access to Document

10.1109/ISBI.2007.356825

Cite this

Nain, D., Styner, M., Niethammer, M., Levitt, J. J., Shenton, M. E., Gerig, G., Bobick, A., & Tannenbaum, A. (2007). Statistical shape analysis of brain structures using spherical wavelets. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings (pp. 209-212). Article 4193259 (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings). https://doi.org/10.1109/ISBI.2007.356825

Statistical shape analysis of brain structures using spherical wavelets. / Nain, D.; Styner, M.; Niethammer, M. et al.
2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. 2007. p. 209-212 4193259 (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nain, D, Styner, M, Niethammer, M, Levitt, JJ, Shenton, ME, Gerig, G, Bobick, A & Tannenbaum, A 2007, Statistical shape analysis of brain structures using spherical wavelets. in 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings., 4193259, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings, pp. 209-212, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07, Arlington, VA, United States, 4/12/07. https://doi.org/10.1109/ISBI.2007.356825

Nain D, Styner M, Niethammer M, Levitt JJ, Shenton ME, Gerig G et al. Statistical shape analysis of brain structures using spherical wavelets. In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings. 2007. p. 209-212. 4193259. (2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings). doi: 10.1109/ISBI.2007.356825

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abstract = "We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions.",

keywords = "Image shape analysis, Wavelet transforms",

author = "D. Nain and M. Styner and M. Niethammer and Levitt, {J. J.} and Shenton, {M. E.} and G. Gerig and A. Bobick and A. Tannenbaum",

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AU - Nain, D.

AU - Styner, M.

AU - Niethammer, M.

AU - Levitt, J. J.

AU - Shenton, M. E.

AU - Gerig, G.

AU - Bobick, A.

AU - Tannenbaum, A.

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N2 - We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions.

AB - We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions.

KW - Image shape analysis

KW - Wavelet transforms

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Statistical shape analysis of brain structures using spherical wavelets

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Keywords

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